Med Teach
Department of Medical Psychology and Psychiatry, School of Medical Sciences, University of Campinas, Campinas, São Paulo, Brazil.
Published: November 2024
Eye tracking has become increasingly applied in medical education research for studying the cognitive processes that occur during the performance of a task, such as image interpretation and surgical skills development. However, analysis and interpretation of the large amount of data obtained by eye tracking can be confusing. In this article, our intention is to clarify the analysis and interpretation of the data obtained from eye tracking. Understanding the relationship between eye tracking metrics (such as gaze, pupil and blink rate) and cognitive processes (such as visual attention, perception, memory and cognitive workload) is essential. The importance of calibration and how the limitations of eye tracking can be overcome is also highlighted.
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http://dx.doi.org/10.1080/0142159X.2024.2316863 | DOI Listing |
Nano Lett
January 2025
School of Environmental and Chemical Engineering, Jiangsu University of Science and Technology, Zhenjiang, Jiangsu 212003, PR China.
Wearable sweat sensors offering real-time monitoring of biomarker levels suffer from stability and accuracy issues, primarily due to low biomarker concentrations, fluctuating sweat pH, and material detachment from sensor deformation. Here, we developed a wearable sensing system integrated with two advanced electrodes and a flexible microchannel for long-term reliable monitoring of sweat pH and uric acid (UA). By printing the ink doped with nanomaterials (CoO@CuCoO and polyaniline), we achieved highly stable electrodes for the direct analysis of perspiration, without additional surface modification.
View Article and Find Full Text PDFComput Biol Med
January 2025
Department of Electrical and Computer Engineering, University of Florida, Gainesville, FL, 32610, United States; Department of Medicine, University of Florida, Gainesville, FL, 32610, United States; Department of Health Outcomes and Biomedical Informatics, University of Florida, Gainesville, FL, 32610, United States; Intelligent Clinical Care Center, University of Florida, Gainesville, FL, 32610, United States. Electronic address:
Retinal image registration is essential for monitoring eye diseases and planning treatments, yet it remains challenging due to large deformations, minimal overlap, and varying image quality. To address these challenges, we propose RetinaRegNet, a multi-stage image registration model with zero-shot generalizability across multiple retinal imaging modalities. RetinaRegNet begins by extracting image features using a pretrained latent diffusion model.
View Article and Find Full Text PDFJ Transl Med
January 2025
School of Information and Communication Engineering, Dalian University of Technology, No. 2 Linggong Road, 116024, Dalian, China.
Background: Parkinson's Disease (PD) is a neurodegenerative disorder, and eye movement abnormalities are a significant symptom of its diagnosis. In this paper, we developed a multi-task driven by eye movement in a virtual reality (VR) environment to elicit PD-specific eye movement abnormalities. The abnormal features were subsequently modeled by using the proposed deep learning algorithm to achieve an auxiliary diagnosis of PD.
View Article and Find Full Text PDFJ Affect Disord
January 2025
School of Psychological Sciences, Tel Aviv University, Tel-Aviv, Israel. Electronic address:
Background: Increased attention allocation to negative-valenced information and decreased attention allocation to positive-valenced information have been implicated in the etiology and maintenance of depression. The Matrix task, a free-viewing eye-tracking attention assessment task, has shown corroborating results, coupled with adequate reliability. Yet, replication efforts are still needed.
View Article and Find Full Text PDFPsychon Bull Rev
January 2025
Department of Psychology, McGill University, 2001 Av. McGill College, Montréal, QC, H3A 1G1, Canada.
A growing body of evidence across psychology suggests that (cognitive) effort exertion increases in proximity to a goal state. For instance, previous work has shown that participants respond more quickly, but not less accurately, when they near a goal-as indicated by a filling progress bar. Yet it remains unclear when over the course of a cognitively demanding task do people monitor progress information: Do they continuously monitor their goal progress over the course of a task, or attend more frequently to it as they near their goal? To answer this question, we used eye-tracking to examine trial-by-trial changes in progress monitoring as participants completed blocks of an attentionally demanding oddball task.
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